The Role of Organizational Slack in Buffering Financially Distressed Hospitals from Market Exits
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The Role of Organizational Slack
in Buffering Financially Distressed Hospitals
from Market Exits
Neeraj Puro, PhD, College of Business, Florida Atlantic University, Boca Raton, Florida;
Nancy Borkowski, DBA, FACHE, School of Health Professions, University of Alabama at
Birmingham, Birmingham, Alabama; Scott Feyereisen, PhD, College of Business, Florida Atlantic
University; Larry Hearld, PhD, School of Health Professions, University of Alabama at Birmingham;
Downloaded from https://journals.lww.com/jhmonline by BhDMf5ePHKav1zEoum1tQfN4a+kJLhEZgbsIHo4XMi0hCywCX1AWnYQp/IlQrHD3i3D0OdRyi7TvSFl4Cf3VC1y0abggQZXdtwnfKZBYtws= on 01/15/2021
Nathaniel Carroll, PhD, School of Health Professions, University of Alabama at Birmingham;
James Byrd, PhD, Collat School of Business, University of Alabama at Birmingham; Dean Smith, PhD,
School of Public Health, Louisiana State University Health Sciences Center, New Orleans, Louisiana;
and Akbar Ghiasi, PhD, H-E-B School of Business and Administration, University of the Incarnate
Word, San Antonio, Texas
EXECUTIVE SUMMARY
Financial distress is a persistent problem in U.S. hospitals, leading them to close at an alarm-
ing rate over the past two decades. Given the potential adverse effects of hospital closures
on healthcare access and public health, interest is growing in understanding more about
the financial health of U.S. hospitals. In this study, we set out to explore the extent to which
relevant organizational and environmental factors potentially buffer financially distressed
hospitals from closure, and even at the brink of closure, enable some to merge with other
hospitals. We tested our hypotheses by first examining how factors such as slack resources,
environmental munificence, and environmental complexity affect the likelihood of survival
versus closing or merging with other organizations. We then tested how the same factors
affect the likelihood of merging relative to closing for financially distressed hospitals that
undergo one of these two events. We found that different types of slack resources and envi-
ronmental forces impact different outcomes. In this article, we discuss the implications of our
findings for hospital stakeholders.
For more information regarding the concepts in this article, please contact Dr. Puro at npuro@fau.edu.
The authors declare no conflicts of interest.
Supplemental digital content is available for this article. Direct URL citations appear in the printed
text and are provided in the HTML and PDF versions of this article on the journal’s website
(www.jhmonline.com).
© 2021 Foundation of the American College of Healthcare Executives
DOI: 10.1097/JHM-D-20-00004
48 Volume 66, Number 1 • January/February 2021
© 2021 Foundation of the American College of Healthcare Executives. All rights reserved.Organizational Slack in Financially Distressed Hospitals
INTRODUCTION obligations to a lender unmet (Zaki et al.,
Financial distress is a common problem in 2011). Researchers have looked at the con-
U.S. hospitals, with some estimates sug- sequences of financial distress on hospitals,
gesting that approximately 15% to 30% of notably public hospitals (Ramamonjiarivelo
the hospitals are classified as “distressed” et al., 2015). However, to date, only one
in any given year (Richards, 2014). Health- study has examined the consequences of
care executives have emphasized the role of financial distress and compared acute care
negative margins, stemming from chang- hospitals that merged, closed, or survived
ing Medicare reimbursements and falling (Bazzoli & Andes, 1995). The study con-
Medicaid margins, in placing increas- cluded that distressed urban hospitals that
ing financial pressures on U.S. hospitals eventually closed were smaller in size and
(American Hospital Association [AHA], had higher outpatient visits compared with
2020; MedPAC, 2016). These financial distressed urban hospitals that merged. Also,
pressures are putting hospitals into finan- the authors reported that hospital competi-
cial distress, eventually leading them to exit tion was higher for distressed hospitals that
their markets. The number of hospitals in closed compared with distressed hospitals
the United States has gradually declined that merged in both rural and urban areas.
because of exits, primarily in the form of However, the study sample consisted of only
closures and consolidation (mergers and 340 community hospitals (19 closures, 11
acquisitions; Harrison, 2007). According mergers, and 310 surviving hospitals), mak-
to the Cecil G. Sheps Center for Health ing it challenging to generalize the results.
Services Research (2020), more than Further, the study considered mergers and
160 rural hospitals closed in the closures as independent events, not as com-
United States between 2005 and 2019 alone. peting events. Another study that compared
Hospitals that close exhibit financial hospital mergers, closures, and surviving
distress relative to those that remain open hospitals found that social capital (mutualis-
(Holmes et al., 2017). Additionally, when tic ties and legitimating ties) buffers hospitals
faced with financial distress, many hospitals from merging or closing (Wells et al., 2001).
likely merge with other hospitals, while others Although our study considered merg-
attempt turnarounds or persist without any ers and closures as competing events, it did
organizational response (Langabeer, 2008). not find any association between the two
Hospital closures lead to lost medical care for with respect to social capital. Most impor-
patients in their counties, which may nega- tantly, our study did not make a clear dis-
tively affect access to healthcare (Zhao, 2007). tinction regarding the extent to which the
Other consequences of hospital closures hospitals were financially distressed before
include rising unemployment rates, increases they merged or closed. This raises the fol-
in the infant mortality rate, increases in unin- lowing question: Why do some hospitals
tentional injuries, and decreased access to choose to persist despite being financially
care for low-income residents (Buchmueller distressed, while other hospitals choose to
et al., 2006; Holmes et al., 2006). close or merge?
Financial distress refers to a period In this article, we extend the concept of
during which a borrower leaves payment business failure in acute care hospitals by
www.ache.org/journals 49
© 2021 Foundation of the American College of Healthcare Executives. All rights reserved.Journal of Healthcare Management
using data collected from a national sample target organization to be an attractive
of short-term acute care hospitals between option to a potential buyer. In the case of
2006 and 2016. We explore distress-related acute care hospitals, regardless of whether
exits (merger and closure) and attempt to FDHs end up choosing different events—
identify organizational and environmental merging, closing, or persisting—we suggest
factors that buffer the hospitals from either that these outcomes are contingent on par-
of these events. We also look at these fac- ticular organizational and environmental
tors and determine the likelihood of one factors. Guided by the competitive strategy
event (merger) occurring over the other literature and previous qualitative studies
(closure) for financially distressed hospitals of FDHs (Langabeer, 2008), we examined
(FDHs). The study findings may have how specific factors buffer FDHs from
implications for a distressed hospital’s merging or closing, as well as how those
stakeholders, including employees, factors affect the likelihood of a merger
patients, lenders, suppliers, the community, over a closure if the organization must
and the economy. undergo one of these two events.
CONCEPTUAL FRAMEWORK Organizational Factors
Financially distressed organizations Slack Resources
may face multiple outcomes that include FDHs, along with other types of organiza-
merging with other organizations, clo- tions, generally have limited amounts of
sure (through bankruptcy or other formal easily deployable resources, also referred to
proceedings), or turnaround (Langabeer, as financial slack. Slack resources exist in a
2008). Turnarounds, although not often continuum, as they range from unabsorbed
successful, typically involve implementing to absorbed slack (Singh, 1986). Unab-
strategies designed to address efficiency sorbed slack generally involves currently
and/or quality concerns; the success of uncommitted resources that are readily
such turnarounds depends not only on the available and easily redeployed within
environmental conditions faced by the hos- organizations (Bourgeois & Singh, 1983).
pital, but also on the availability of specific The most easily redeployed resources
types of internal resources and capabilities typically are cash resources, over which
(Langabeer, 2008). Alternatively, an orga- managers have the greatest discretion in
nization could choose to persist without terms of allocation (George, 2005; Greve,
undertaking any of these responses. 2003). We expect unabsorbed slack to buf-
Although a turnaround strategy can fer the hospitals from merging or closing.
help the hospital retain its organizational Alternatively, absorbed slack is defined
identity and alleviate financial distress, as resources that may be recoverable but
administrators may find it challenging to might already have been utilized in cur-
reverse the fortunes of an underperform- rent operations; recovering these resources
ing organization overnight. However, if an requires additional managerial time and
organization decides to exit the market via effort. Examples are human resources,
a closure, it is considered a single-sided overhead expenses, and accounts receiv-
event; in contrast, a merger requires the able (Bourgeois & Singh, 1983; Greve,
50 Volume 66, Number 1 • January/February 2021
© 2021 Foundation of the American College of Healthcare Executives. All rights reserved.Organizational Slack in Financially Distressed Hospitals
2003; Voss et al., 2008). Along this con- or merger partner. A debt level that is too
tinuum lies potential slack. high might decrease the attractiveness of
Potential slack is slack that can be more an organization as an acquisition candi-
difficult and potentially less desirable to date (Pastena & Ruland, 1986). We believe
convert to an easily deployable form; it can that high-debt leverage may increase the
be called the slack of last resort. It reflects likelihood of both a merger and a closure
the extent to which assets can be converted for FDHs. However, in the face of turbulent
to liquid form, and it can be measured healthcare environments, hospitals will be
in terms of the debt-to-equity ratio, or deterred from taking risky strategies such
debt leverage (total liabilities/total assets; as merging with another hospital that has
Vanacker et al., 2017). For example, if a high-debt leverage, making merger over a
hospital owned buildings, this construct closure less likely for FDHs.
would measure the extent to which selling
the property and leasing it back would free System Membership
up cash, or the extent to which the orga- Group membership is another source of
nization can take out debt, enabling it to potential slack (Ringlstetter, 1995) By
monetize its equity for use in operations. forming an internal capital market that
Given the distressed state of hospitals in allows resources to be reallocated across
our study and their perceived need to use hospitals to facilitate mobilization of
all means necessary to survive, we can slack resources, organizations can buffer
expect that this type of slack, in different underperforming hospitals from merging
forms, will affect FDH events. or closing (Shin & Stulz, 1998). For hospi-
tals, group membership can include being
Debt Leverage part of a bigger system. Being a part of a
Drawing on Langabeer’s (2008) in-depth system may help in quickly moving the
analysis of individual FDHs, we can infer collection of intragroup receivables to the
that debt leverage has the potential to hospitals that face unexpected cash short-
influence organizations’ merger or closure ages (Deloof & Jegers, 1996). Avoiding the
decisions. Specifically, high-debt leverage loss of reputation is another reason why
can make an organization vulnerable to systems may resist closing underperform-
competitors’ aggressive behavior ing hospitals. Liquidation of a subsidiary
(Langabeer, 2008; Majumdar et al., 2016). may result in a considerable loss of repu-
However, this scenario may help the tation for the parent organization (Prantl,
distressed organization with high levels 2003). Consequently, a hospital system
of debt receive a better buyout price may persist with the underperforming
from a rival, even when it is unprofitable hospital or find a merging partner for
(Balcaen et al., 2012). In contrast, high it instead of allowing it to close. Group
leverage may decrease the likelihood of a membership has a positive influence on
merger. Balcean et al. (2012) explained that the likelihood of finding a merger partner
exceedingly high debt levels due to finan- because of the presence of many partici-
cial deterioration will make it difficult for pants in a group or network who may help
organizations to find a suitable takeover find a potential buyer or merger partner
www.ache.org/journals 51
© 2021 Foundation of the American College of Healthcare Executives. All rights reserved.Journal of Healthcare Management
(Balcaen et al., 2012). Therefore, we capacity) for the organization (Sutcliffe,
hypothesize here that 1994). A high degree of munificence can
provide a necessary cushion to organiza-
Hypothesis 1a (H1a): Slack (unab- tions in the form of financial and profes-
sorbed or potential) will buffer FDHs sional slack that will help facilitate both
from both merging with other organi- stability and growth (Andrews & Johansen,
zations and closing. 2012). In contrast, environmental scarcity
can aggravate the likelihood of both merg-
Hypothesis 1b (H1b): Given the neces- ers and closures because of the insuffi-
sity of either merging or closing, FDHs ciency of resources to support an existing
with higher levels of slack (unabsorbed hospital. However, environmental munifi-
or potential) will be more likely to cence should increase the likelihood of a
merge than to close. merger rather than a closure if there is a
choice between the two events. From an
Environmental Factors acquirer’s perspective, the FDH in a scarce
In addition to slack resources that are inter- environment may not be an attractive
nal to an organization, certain environmen- target for a merger because of the inad-
tal factors can buffer hospitals from merging equacy of future earning potential.
or closing when faced with financial distress.
Organizations depend on the resources Hypothesis 2a (H2a): Environmen-
within their environments to operate (Pfeffer tal munificence will have a positive
& Salancik, 2003). Scarce resources or an influence on buffering FDHs from
uncertain environment places an additional both merging with other organiza-
challenge on managers to act in ways that tions and closing.
enable them to secure resources and reduce
uncertainty. Resource dependency theory Hypothesis 2b (H2b): Given the
provides a framework for measuring the necessity of merging or closing, FDHs
environmental constructs of munificence operating in munificent environments
and complexity. Munificence refers to the are more likely to merge than to close.
availability of critical resources in the orga-
nization’s environment, while complexity Environmental Complexity
pertains to the uncertainty, heterogeneity, Environmental complexity refers to the
or diversity in the environment. A hospital’s degree of heterogeneity within the market
decision to merge, close, or persist when fac- (Dess & Beard, 1984). A heterogeneous
ing financial distress may be associated with environment contains a large number of
the level of environmental munificence and diverse entities, which adds to the uncer-
complexity. tainty in the environment, as organizations
need to compete with too many players for
Environmental Munificence access to critical resources. Also, a com-
Munificence is defined as the availability plex environment may produce informa-
of resources in the environment that will tion uncertainty for decision-makers.
support sustained stability or growth (i.e., Complex environments as measured by
52 Volume 66, Number 1 • January/February 2021
© 2021 Foundation of the American College of Healthcare Executives. All rights reserved.Organizational Slack in Financially Distressed Hospitals
competitiveness may affect the exit out- Health Services Research data as sources.
come for FDHs. FDHs in less competitive We considered hospitals that closed to be
markets will likely persist rather than merge financially distressed at the time of the event
or close. However, less competitive markets if their Altman Z score was below 1.8.
may increase the likelihood of a merger We considered hospitals that did not
compared with a closure. From an acquirer’s merge or close to be persisting hospi-
perspective, merging with a single entity in a tals that were financially distressed. To
fragmented market would yield a less com- determine the Altman Z score, we used
petitive advantage (Wells et al., 2001). the Healthcare Cost Report Information
System from the Centers for Medicare &
Hypothesis 3a (H3a): Environmen- Medicaid Services, which provides data
tal complexity will have a negative on financial performance measures. The
influence on buffering FDHs from Healthcare Cost Report Information Sys-
both merging with other organiza- tem data set contains hospitals’ utilization,
tions and closing. cost, and charge data (Kane & Magnus,
2001). Also, the AHA survey provided
Hypothesis 3b (H3b): Given the need data about organizational characteristics,
to either merge or close, FDHs operat- including health system membership,
ing in more complex environments are size, and ownership type. The Area Health
more likely to merge than to close. Resources Files provided data regarding
county-level market characteristics of hos-
METHODS pitals (Hart et al., 2005).
Data
Our study drew on secondary data from Analysis
multiple sources. For mergers, we relied on Dependent Variables
2006 to 2016 data from the AHA Annual In this study, we were interested in
Survey of Hospitals (n.d.) extracted from hospitals’ prospects for merging with
Wharton Research Data Services (2020) other hospitals or closing. Therefore,
and the hospital acquisition report from merging included acquisitions and
Irving Levin Associates (n.d.), which consolidations. We coded a hospital as
contains data that tracks hospital merg- having been merged or acquired when
ers and acquisitions on a yearly basis. it changed its name and its AHA survey
Mergers included hospitals that merged identification code to that of the acquir-
with another hospital and those that were ing entity. Consolidation occurred when
acquired by another hospital or health sys- a hospital added the name of another
tem. We further segregated target hospitals hospital to its own, and when the other
that merged on the basis of whether they hospital reported the same change. We
were financially distressed at the time of the coded a hospital as having closed when it
merger. An Altman Z score below 1.8 was reported permanently ceasing all hospital
considered a measure of financial distress. care functions. The third group consisted
For closures, we used the AHA annual of hospitals that persisted even when
survey and the Cecil G. Sheps Center for financially distressed.
www.ache.org/journals 53
© 2021 Foundation of the American College of Healthcare Executives. All rights reserved.Journal of Healthcare Management
Independent Variables the number of Medicaid inpatient days to
Organizational factors. Debt leverage (H1) total inpatient days, and Medicare payer
was measured as the ratio of total liabilities mix is the ratio of the number of Medicare
to total assets, while cash holdings were inpatient days to total inpatient days.
measured using hospitals’ cash and cash
equivalents. Health care system member- Model and Estimation
ship (H1) was coded as a binary variable, To determine how organizational and
and coded “0” if the hospital was not a part environmental factors affect three distinct
of the system and “1” if the hospital was a outcomes, we included the same set of
system member. covariates and ran three separate logistic
regression models in predicting the com-
Environmental factors. Environmental peting risks of (1) closure versus nonevent,
munificence (H2) was operationalized using (2) merger versus nonevent, and (3) merger
three variables: (1) the percentage of the versus closure. The assumption made is
population eligible for Medicare in the that parallel events unfold in sequence,
hospital’s county, (2) the county’s unem- where a hospital first faces an undesirable
ployment rate, and (3) the location of the event—either merge with another hospital
hospital (Menachemi et al., 2012; Tarver & or close—and then attempts to minimize
Menachemi, 2018). Environmental com- that event by merging rather than clos-
plexity (H3) was operationalized using the ing (Wells et al., 2001). For model 1, the
Herfindahl–Hirschman index (HHI) (Hsieh event was closing and the nonevent was
et al., 2010; Zinn et al., 1998) and Medicare- persisting with financial distress without
managed care penetration as variables. The any organizational response (hospitals that
HHI is a common measure of the market merged were excluded). For model 2, the
concentration and is calculated as a ratio event was merging and the nonevent was
of the number of hospital admissions in a persisting with financial distress without
given year to the county’s hospital admis- any organizational response (hospitals that
sions in a given year. closed were excluded). For model 3, the
event was merging and the nonevent was
Controls closing (hospitals that did not merge or
We measured hospital size according to close were excluded). Model 3 thus exam-
the number of staffed beds. We categorized ined the factors that affected the likelihood
hospital ownership as nonfederal govern- of merging versus closing for FDHs, given
ment, nongovernment not-for-profit, and that one of these two events occurred. For
for-profit. Teaching status of the hospital the first two hypotheses, we used general-
was categorized as a binary variable (1 if ized estimating equations to avoid biases
the hospital was a part of the Council of due to correlation within individual hospi-
Teaching Hospitals and Health Systems, tals across time (Liang & Zeger, 1986). For
0 if otherwise). We calculated payer mix model 3, because each hospital was only
as the proportion of patients with Med- in this data set once, there was no concern
icaid or Medicare coverage (Yeager et al., about autocorrelation; we therefore used
2015). Medicaid payer mix is the ratio of regular logistic regression.
54 Volume 66, Number 1 • January/February 2021
© 2021 Foundation of the American College of Healthcare Executives. All rights reserved.Organizational Slack in Financially Distressed Hospitals
RESULTS were located in urban areas, and only 5%
Table 1 provides the descriptive statistics were members of the Council of Teaching
for all of the hospitals in our data set. There Hospitals and Health Systems.
were 11,395 hospital-year observations. Table 2 presents the descriptive statis-
The mean Medicare-managed penetration tics of the subset of hospitals that closed
rate was 21.77%, and the mean level of (n = 100) or merged (n = 70). Descriptive
market fragmentation (HH1) was 0.72 on a statistics for the subset of hospitals that
scale from 0 to 1, indicating the presence of merged or closed during the study period
dominant market shares. For the organiza- do not reveal substantial differences from
tional variables, about 60% of the hospitals the broader sample of 11,395 hospital-year
belonged to systems. The average occu- observations. The hospitals that merged
pancy rate of the hospitals was 52.3%. In had an average leverage of 1.2, whereas
terms of ownership, 52.72% of the hospitals hospitals that closed had a slightly higher
were not-for-profit, 26.04% were for-profit, average leverage of 1.7. Again, 46.5% of
and 21.24% were non-federal government the hospitals in this subsample belonged
hospitals. More than 60% of the hospitals to a system. The mean level of market
TABLE 1
Descriptive Statistics: All Financially Distressed Acute Care Community Hospital-Years
(N = 11,395)
Variable Observations M SD Minimum Maximum
Slack resources
Cash holdings, $ 11,395 3,310,000 8,550,000 –5,780,000 6.79e + 07
Leverage 11,395 1.124 .989 –272 7.512
System membership 11,395 .587 .492 0 1
Environmental scarcity
Unemployment rate 11,395 7.174 2.753 0 22.9
Population eligible for 11,395 19.057 54.088 .382 1,308.573
Medicare, %
Location (urban) 11,395 .607 .489 0 1
Environmental complexity
Managed care penetration 11,395 21.78 14.25 0 65.23
HHI 11,395 .721 .342 .041 1
Control variables
No. of staffed beds 11,395 147.27 173.868 0 2,700
Ownership 11,395 .685 .8 0 2
Teaching status 11,395 1.947 .224 1 2
Occupancy rate 11,395 .524 .241 .003 6.593
Medicare payer mix 11,395 14.991 16.389 0 98.957
Medicaid payer mix 11,395 39.365 27.259 0 235
Note. HHI = Herfindahl–Hirschman index.
www.ache.org/journals 55
© 2021 Foundation of the American College of Healthcare Executives. All rights reserved.Journal of Healthcare Management
TABLE 2
Descriptive Statistics: Financially Distressed Hospitals That Merged or Closed (N = 170)
Mergers (n = 70) Closures (n = 100)
Variable M SD M SD
Slack resources
Cash holdings, $ 2,270,000 5,120,000 1,100,000 3,560,000
Leverage 1.123 .62 1.717 1.227
System membership .7 .462 .44 .499
Environmental scarcity
Unemployment rate 7.417 2.245 8.01 3.164
Population eligible for Medicare, % 15.58 17.505 14.635 4.025
Location (urban) .829 .38 .63 .485
Environmental complexity
Managed care penetration 23.364 12.215 22.203 12.989
HHI .621 .356 .681 .377
Control variables
No. of staffed beds 150.286 109.244 90.01 93.904
Ownership .5 .608 .72 .697
Teaching status .057 .234 .01 .1
Occupancy rate .579 .193 .433 .201
Medicare payer mix 16.535 17.53 14.089 11.338
Medicaid payer mix 44.318 24.224 44.243 25.859
Note. HHI = Herfindahl–Hirschman index.
fragmentation (HHI) in the subsample more likely to merge than to close. Our
was 0.651 on a scale from 0 to 1, indicating findings supported this hypothesis for
more moderate market shares. potential slack; an increase in debt leverage
Table 3 lists the coefficients and was associated with a decrease in the likeli-
standard errors from our logistic regres- hood of a merger compared with a closure
sion analysis. The study findings partially (p < .01). Also, being affiliated with a sys-
support H1a, which states that FDHs with tem increased the likelihood of a merger
slack resources (unabsorbed or potential) compared with a closure (p < .01).
are less likely to close compared with those The study findings reveal partial sup-
that persist. The findings suggest that port for H2a: FDHs operating in munifi-
FDHs with higher cash holdings (p < .1), cent environments were less likely to close
lower leverage (p < .01), and system mem- (p < .05). However, the study findings did
bership (p < .01) were less likely to close not show any association between envi-
than persist. However, we did not find any ronmental munificence and the choice of a
association between slack resources and merger over a closure (H2b). In addition,
the likelihood of merging compared with FDHs in areas with higher unemployment
persisting. According to H1b, FDHs with rates (p < .05) and in rural areas (p < 0.1)
higher levels of slack resources would be were more likely to close. Environmental
56 Volume 66, Number 1 • January/February 2021
© 2021 Foundation of the American College of Healthcare Executives. All rights reserved.Organizational Slack in Financially Distressed Hospitals
TABLE 3
Logistic Regression Models: Effects of Covariates on Merging and Closing
Closure vs. No Event Merger vs. No Event Merger vs. Closure
Parameter Standard Parameter Standard Parameter Standard
Variable Estimate Error Estimate Error Estimate Error
Slack resources
Cash holdings 0.000* 0.000 0.000 0.000 0.000 0.000
Leverage 0.349*** 0.062 −0.030 0.127 0.789*** 0.245
System membership −0.704*** 0.217 0.246 0.273 −1.121*** 0.405
Environmental munificence
Unemployment rate 0.088** 0.035 0.039 0.046 0.070 0.082
Population 65 years or −0.008 0.013 −0.002 0.005 −0.016 0.033
older, %
Location 0.440* 0.262 1.188*** 0.365 −0.749 0.518
Environmental complexity
Managed care penetration 0.005 0.008 −0.006 0.010 0.021 0.016
Market competition −0.749** 0.328 −0.539 0.374 −0.012 0.598
(HHI)
Control factors
No. of staffed beds −0.003** 0.001 −0.002 0.001 −0.002 0.002
Ownership −0.124 0.138 −0.255 0.183 0.253 0.314
Teaching status −0.541 1.056 −0.259 0.595 1.175 1.347
Occupancy rate −1.314** 0.589 0.484 0.358 −2.877** 1.137
Medicare payer mix 0.006 0.007 0.007 0.008 −0.001 0.014
Medicaid payer mix 0.003 0.004 −0.002 0.001 −0.012 0.008
Note. HHI = Hirschman-Herfindahl index.
*p ≤ .1. **p ≤ .05. ***p ≤ .01.
complexity, as measured by the level of unrelated to mergers. However, higher
market fragmentation (HHI), was associ- occupancy rates favored mergers over clo-
ated with the likelihood of merging (p < .05) sures (p < .01). Regarding the hospitals that
and the likelihood of closing (p < .01), persisted, we ran a survival analysis to see
providing support for H3a. However, there the length of time a hospital could sustain
was no association between environmental operations in financial distress and found
complexity and the likelihood of mergers hospitals that persisted through all 11 years
relative to closures (H3b). Smaller hospi- in the data. The survival analysis is pub-
tals (in number of beds) were more likely lished online as Supplemental Digital Con-
to close than larger hospitals; however, tent at http://links.lww.com/JHM/A46.
the study findings showed no association
between hospital size and the likelihood of DISCUSSION
a merger. Higher occupancy rates reduced The purpose of this study was to examine
the likelihood of closures, but were which organizational and environmental
www.ache.org/journals 57
© 2021 Foundation of the American College of Healthcare Executives. All rights reserved.Journal of Healthcare Management
factors buffer FDHs from merging or of property as part of a merger because of
closing and enable them to persist in the high leverage.
market. In addition, we looked for factors Potential slack in another form also
that were associated with the likelihood influenced mergers over closures. FDHs
of a merger over a closure for FDHs. The that were part of a healthcare system were
overall findings of this study suggest that more likely to merge than close. System
slack resources, environmental munifi- members may find merging partners and
cence, and environmental complexity avoid closure. Hospitals that closed were
likely play roles in whether hospitals not affiliated with any system. This study
persist, choose mergers, or close. points to the increasing influence of health
Measures of organizational slack that systems in the United States and gives
involve cash holdings and debt leverage researchers additional direction in explor-
helped FDHs persist in the market. These ing how health systems manage financial
findings lend support to the idea that distress in individual hospitals.
unabsorbed and potential slack impact the Our findings raise important issues
ability of FDHs to navigate turbulent times. regarding potential hospital responses to
System membership, another measure financial distress. Little attention has been
of potential slack, also was significantly given to how the organizational and envi-
associated with outcomes for FDHs. This ronmental factors buffer FDHs from merg-
finding was validated by a study that found ing or closing. One significant finding is
that rural hospital closures were positively that slack resources play an important role
correlated with lack of system membership in buffering hospitals from closing. FDHs
(Mullner & Whiteis, 1988). that have too much debt leverage may
Environmental factors that buffer eventually have to exit the market through
FDHs from closing include a low unem- a closure that affects the entire community.
ployment rate and low competition. In this High debt leverage also may reduce the
study, a higher number of staffed beds and attractiveness of a hospital to a potential
low occupancy rates also cushioned hospi- merging partner.
tals from closing. However, we did not find In addition, our study findings add
many organizational and environmental information about how hospitals’ response
factors that buffered FDHs from merging to financial distress is related to environ-
relative to persisting with no organiza- mental factors. FDHs operating in munifi-
tional response. Only the level of market cent environments are less likely to close.
fragmentation (HHI) was negatively asso- Policymakers in charge of Centers for
ciated with rates of merging. These results Medicare & Medicaid Services reimburse-
show that low potential slack, in the form ment programs should take these factors
of high debt leverage, decreases the likeli- into consideration and increase reimburse-
hood of a merger over a closure. FDHs ment for hospitals in environments with
with exceeding amounts of debt leverage scarce resources if they do not want them
may be less attractive targets for mergers to close. Hospital leaders may apply the
or a suitable takeover. Also, creditors may variables in this study to examine their
be cautious or even oppose the transfer own internal organizations’ capacity and
58 Volume 66, Number 1 • January/February 2021
© 2021 Foundation of the American College of Healthcare Executives. All rights reserved.Organizational Slack in Financially Distressed Hospitals
perform environmental scanning when Cecil G. Sheps Center for Health Services Research.
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www.shepscenter.unc.edu/programs-projects/
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Practitioner Application:
The Role of Organizational Slack in Buffering Financially
Distressed Hospitals From Market Exits
James Langabeer, PhD, FACHE, vice chair of population health, Department of Emergency
Medicine and professor of healthcare management, The University of Texas Health Science Center,
Houston, Texas
T
he financial viability of our nation’s hospital facilities needs to be a significant
concern for both practitioners and researchers. Very few new hospitals open in any
given year, while hundreds have closed or merged over the past decade. Closures
and mergers can lead to a shrinking supply of organizations and capacity, especially in
rural and underserved areas. Puro and colleagues used multiple longitudinal data sources
and a robust research framework in this study to gain insight into the levels of financial
distress across U.S. hospitals.
When hospitals begin to fail financially, there are major consequences to the surrounding
community, and that phenomenon tends to further impair neighborhoods and local econo-
mies. Numerous factors contribute to closures, such as poor market location, lack of adequate
competitive strategy, turbulent environment, poor management, and inability to retain suffi-
cient capital necessary for plant and technology investments, among others. In this study, the
authors found evidence of 170 merged or closed facilities during a 10-year period. Differences
between those facilities that closed versus those that remained viable suggest some significant
patterns. Those that closed had higher debt ratios, less cash on hand, and were less likely to be
part of a system.
The author declares no conflicts of interest.
© 2021 Foundation of the American College of Healthcare Executives
DOI: 10.1097/JHM-D-20-00306
www.ache.org/journals 61
© 2021 Foundation of the American College of Healthcare Executives. All rights reserved.Journal of Healthcare Management
All hospital leaders can learn from the results of this study. Of note, financial distress
does not need to be permanent. A variety of strategic, operational, and financial maneu-
vers can alleviate distress; effective turnarounds are possible. Turnarounds, or a return
to financial recovery, involve carefully identifying steps to evade collapse. Yet, this will
require proactive leaders who can navigate the complexities of identifying network and
system partners, implementing quality and process improvement practices, and restruc-
turing bonds and other debt tools. A comprehensive approach to managing financially
distressed facilities calls for committed leaders who understand drivers of revenue cycle,
supply chain, marketing, and human resources. Turnarounds to convert a distressed
hospital into a financially viable one are possible; bankruptcy is not the only fate. Frequently,
consultants are necessary to help pave a clear turnaround path.
The authors point to organizational slack and the importance of participating in a
health system as important variables to avoid distress. In addition, identifying potential
partners such as medical schools is equally strategic in navigating in today’s environment.
Maybe the most important lesson we can take away from this article is that financial
distress is complex and multifactorial. For most hospitals, poor financial situations
develop over the course of years, and it can take that long to resolve them. Bankruptcy
filings are not inevitable. Changes in the strategic, operational, and financial response
to the distress can provide effective alternatives in maneuvering through these difficult
times.
62 Volume 66, Number 1 • January/February 2021
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